Tripp Shealy
Virginia Tech

Abstract

This paper introduces three case-based modules for teaching civil engineering students about decision making for sustainability. The purpose of these modules is to connect civil engineering design to recent advances in behavioral decision science. Students who recognize their own decision biases will be better able to manage their decisions and be better able to recognize how their designs influence stakeholder decisions in the future. The three case studies varied in design topic and behavioral decision science concepts, from land development (choice overload) to renewable energy (status quo bias) to wastewater infrastructure (risk aversion). The case-based modules were developed using structured interviews with engineering design teams from each of the case projects. Relevant concepts from behavioral decision science were identified while interviewing the engineering design teams. The developed modules were tested with over 280 undergraduate engineering students. Methods to evaluate learning include pre and post-module surveys and free-response questions. After the module, students were more likely to mention and articulate the role that humans’ mental barriers, like choice overload, bounded rationality, and satisficing play in decision making for sustainability. They also recognized how tools like Envision can help reduce these cognitive biases. In addition to integrating diverse topics and disciplines into a unified and relevant teaching module, the intention is that other faculty can also use these cases. Slides (either one or two-day instruction), teaching notes, and grading rubrics are available for other instructors to download and use and can be found in the Center for Sustainable Engineering repository.

EndNote - RIS

TY - CPAPER
AB - This paper introduces three case-based modules for teaching civil engineering students about decision making for sustainability. The purpose of these modules is to connect civil engineering design to recent advances in behavioral decision science. Students who recognize their own decision biases will be better able to manage their decisions and be better able to recognize how their designs influence stakeholder decisions in the future. The three case studies varied in design topic and behavioral decision science concepts, from land development (choice overload) to renewable energy (status quo bias) to wastewater infrastructure (risk aversion). The case-based modules were developed using structured interviews with engineering design teams from each of the case projects. Relevant concepts from behavioral decision science were identified while interviewing the engineering design teams. The developed modules were tested with over 280 undergraduate engineering students. Methods to evaluate learning include pre and post-module surveys and free-response questions. After the module, students were more likely to mention and articulate the role that humans’ mental barriers, like choice overload, bounded rationality, and satisficing play in decision making for sustainability. They also recognized how tools like Envision can help reduce these cognitive biases. In addition to integrating diverse topics and disciplines into a unified and relevant teaching module, the intention is that other faculty can also use these cases. Slides (either one or two-day instruction), teaching notes, and grading rubrics are available for other instructors to download and use and can be found in the Center for Sustainable Engineering repository.
AU - Nathan McWhirter
AU - Tripp Shealy
CY - Salt Lake City, Utah
DA - 2018/06/23
PB - ASEE Conferences
TI - Development and Assessment of Three Envision Case Study Modules Connecting Behavioral Decision Science to Sustainable Infrastructure
UR - https://peer.asee.org/30314
ER -